Clinical characteristics and outcomes of chronic subdural hematoma in patients with a history of antiplatelet therapy

Yu, Xiaofan; Wu, Liang; Ou, Yunwei; Xu, Liang; Guo, Xufei; Yang, Cheng; Liu, Weiming

doi:10.1016/j.clineuro.2021.106817

Cited by 3 publications

(3 citation statements)

References 25 publications

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“…In a meta-analysis review of randomized trials, Bakheet et al ( 27 ) showed that the incidence of subdural hematoma was greater in patients using dual antiplatelet drugs than in those using aspirin alone. In contrast, in a retrospective study with a large sample size, Yu et al ( 28 ) reported that antiplatelet therapy did not affect the recurrence rate of CSDH. In a systematic review by Nathan et al ( 6 ), the use of anticoagulant medication was concluded to be associated with an increased re-bleeding risk with CSDH, but antiplatelet medication was not.…”

Section: Discussionmentioning

confidence: 88%

Effect of decreased platelets on postoperative recurrence of chronic subdural hematoma

Yagi,

Matsubara,

Kanda

et al. 2023

Front. Neurol.

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IntroductionChronic subdural hematoma (CSDH) is commonly treated using simple burr hole surgery. However, postoperative recurrence occurs at a relatively high rate of 10–20%. A decrease in platelet count (PC) may be associated with recurrence via a hemostasis disorder; however, this association has not been well-studied. Therefore, this study aimed to investigate the association between PC and postoperative CSDH recurrence.MethodsWe retrospectively reviewed the data for CSDHs in 488 cerebral hemispheres of 431 patients who underwent burr hole surgery at our institution between January 2013 and December 2022. The association between preoperative PC and postoperative CSDH recurrence was investigated. We used the first quartile of PC, PC < 170 × 103/μL to define a threshold for decreased PC.ResultsIn total, 459 cerebral hemispheres with CSDHs in 405 patients were followed up postoperatively for at least 3 months or until CSDH disappeared. CSDH recurred in 39 (8.5%) cerebral hemispheres. The recurrence rate was gradually increased in parallel with a decreasing PC. Among 109 CSDHs with a decreased PC (<170 × 103/μL), 15 (13.8%) recurred, whereas only 24 (6.9%) of 350 CSDHs without a decreased PC recurred (p = 0.03). In univariable logistic analysis, eosinophil-rich blood (≥100/μL eosinophils in peripheral blood) and a decreased PC were significant risk factors. Multivariable analysis showed that eosinophil-rich blood (adjusted odds ratio, 2.51; 95% confidence interval, 1.26–4.99; p = 0.009) and a decreased PC (adjusted odds ratio, 2.15; 95% confidence interval, 1.07–4.35; p = 0.03) were independent risk factors for recurrence.ConclusionOur study showed that a decrease in PC was associated with postoperative CSDH recurrence. Patients with CSDH and a decreased PC require careful postoperative follow-up.

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Section: Discussionmentioning

confidence: 88%

Effect of decreased platelets on postoperative recurrence of chronic subdural hematoma

Yagi,

Matsubara,

Kanda

et al. 2023

Front. Neurol.

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“…Fibrinogen, a key clotting factor, may be linked to clotting disorders or hypercoagulability affecting CSDH recurrence ( 31 ). Abnormal TT could signal coagulation disorders, predisposing individuals to recurrent bleeding ( 32 ). HWD directly reflects hematoma size and influences recurrence.…”

Section: Discussionmentioning

confidence: 99%

Synthetic minority over-sampling technique-enhanced machine learning models for predicting recurrence of postoperative chronic subdural hematoma

Ni,

Zhu,

Qian

et al. 2024

Front. Neurol.

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ObjectiveChronic subdural hematoma (CSDH) is a neurological condition with high recurrence rates, primarily observed in the elderly population. Although several risk factors have been identified, predicting CSDH recurrence remains a challenge. Given the potential of machine learning (ML) to extract meaningful insights from complex data sets, our study aims to develop and validate ML models capable of accurately predicting postoperative CSDH recurrence.MethodsData from 447 CSDH patients treated with consecutive burr-hole irrigations at Wenzhou Medical University’s First Affiliated Hospital (December 2014-April 2019) were studied. 312 patients formed the development cohort, while 135 comprised the test cohort. The Least Absolute Shrinkage and Selection Operator (LASSO) method was employed to select crucial features associated with recurrence. Eight machine learning algorithms were used to construct prediction models for hematoma recurrence, using demographic, laboratory, and radiological features. The Border-line Synthetic Minority Over-sampling Technique (SMOTE) was applied to address data imbalance, and Shapley Additive Explanation (SHAP) analysis was utilized to improve model visualization and interpretability. Model performance was assessed using metrics such as AUROC, sensitivity, specificity, F1 score, calibration plots, and decision curve analysis (DCA).ResultsOur optimized ML models exhibited prediction accuracies ranging from 61.0% to 86.2% for hematoma recurrence in the validation set. Notably, the Random Forest (RF) model surpassed other algorithms, achieving an accuracy of 86.2%. SHAP analysis confirmed these results, highlighting key clinical predictors for CSDH recurrence risk, including age, alanine aminotransferase level, fibrinogen level, thrombin time, and maximum hematoma diameter. The RF model yielded an accuracy of 92.6% with an AUC value of 0.834 in the test dataset.ConclusionOur findings underscore the efficacy of machine learning algorithms, notably the integration of the RF model with SMOTE, in forecasting the recurrence of postoperative chronic subdural hematoma. Leveraging the RF model, we devised an online calculator that may serve as a pivotal instrument in tailoring therapeutic strategies and implementing timely preventive interventions for high-risk patients.

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“…This study did not separate immediate outcomes compared with outcomes analyzed at the 6-month follow-up. 14 This could result in additional injuries occurring resulting in poor outcome measures. Furthermore, good outcome was defined as mRS 0-3 which is different from our study and Ducruet et al study, where good outcome was defined as mRS ≤ 2.…”

Section: Discussionmentioning

confidence: 99%

Outcome of Chronic Subdural Hematoma Intervention in Patients on Long-Term Antiplatelet Therapy—A Propensity Score Matched Analysis

et al. 2023

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BACKGROUND: Patients presenting with chronic subdural hematomas (cSDHs) and on antiplatelet medications for various medical conditions often complicate surgical decision making. OBJECTIVE: To evaluate risks of preprocedural and postprocedural antiplatelet use in patients with cSDHs. METHODS: Patients with cSDH who were treated between January 2006 and February 2022 at a single institution with surgical intervention were identified. A propensity score matching analysis was then performed analyzing length of hospitalization, periprocedural complications, reintervention rate, rebleeding risk, and reintervention rates. RESULTS: Preintervention, 178 patients were on long-term antiplatelet medication and 298 were not on any form of antiplatelet. Sixty matched pairs were included in the propensity score analysis. Postintervention, 88 patients were resumed on antiplatelet medication, whereas 388 patients did not have resumption of antiplatelets. Fifty-five pairs of matched patients were included in the postintervention propensity score analysis. No significant differences were found in length of hospitalization (7.8 ± 4.2 vs 6.8 ± 5.4, P = .25), procedural complications (3.3% vs 6.7%, P = .68), or reintervention during the same admission (3.3% vs 5%, P = 1). No significant differences were seen in recurrence rate (9.1% vs 10.9%, P = 1) or reintervention rate after discharge (7.3% vs 9.1%, P = 1) in the postintervention group. CONCLUSION: Preintervention antiplatelet medications before cSDH treatment do not affect length of hospitalization, periprocedural complications, or reintervention. Resumption of antiplatelet medication after cSDH procedures does not increase the rebleeding risk or reintervention rate.

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Clinical characteristics and outcomes of chronic subdural hematoma in patients with a history of antiplatelet therapy

Cited by 3 publications

References 25 publications

Effect of decreased platelets on postoperative recurrence of chronic subdural hematoma

Effect of decreased platelets on postoperative recurrence of chronic subdural hematoma

Synthetic minority over-sampling technique-enhanced machine learning models for predicting recurrence of postoperative chronic subdural hematoma

Outcome of Chronic Subdural Hematoma Intervention in Patients on Long-Term Antiplatelet Therapy—A Propensity Score Matched Analysis

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